Inflammatory cytokines and malnutrition as related to risk for cardiovascular disease in hemodialysis patientsThis article is one of a selection of papers published in the special issue Bridging the Gap: Where Progress in Cardiovascular and Neurophysiologic Research Meet.
Bibliographic record
Abstract
Malnutrition and inflammation are associated with end-stage renal disease (ESRD). Interleukin (IL)-6 and tumor necrosis factor alpha (TNF-alpha) powerfully predict death from cardiovascular disease. The aim of our study was to establish an association between markers of inflammation and parameters of malnutrition in patients on hemodialysis. The study population consisted of 42 hemodialysis patients with different parameters of malnutrition. Blood samples were taken after an overnight fast, and plasma lipid profiles (total cholesterol, LDL cholesterol, HDL cholesterol, and triglycerides) were measured by using conventional enzymatic methods. Serum urea and creatinine levels were also measured by routine procedures. Plasma high-sensitivity C-reactive protein level (hs-CRP), TNF-alpha, and IL-6 were measured by enzyme-linked immunosorbent assay (ELISA). Standard Doppler echo examinations were used to determine plaque on carotid arteries, and end-diastolic diameter (EDD) and ejection fraction (EF) were measured by echocardiography. Malnourished patients exhibited significantly greater evidence of cardiovascular disease and carotid plaques. Factor (principal component) analysis indicated 6 latent factors with 67.5% of the variance explained within all investigated parameters. Cluster analysis was used to distinguish the inflammatory markers and the nutritional markers from other parameters and to visualize similarities between variables. In summary, this cross-sectional study in hemodialysis patients found a high prevalence of malnutrition, inflammation, carotid plaques, and cardiovascular disease. Malnourished dialysis patients are more often found with cardiovascular disease and carotid plaques. In addition, these patients have higher levels of inflammatory cytokines, which may partly explain the elevated risk for atherosclerotic vascular disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".